Classic large-scale computer network architectures having hundreds or thousands of network elements, such as bridges, routers, and switches, are typically managed by a single, centralized network management server, which, by itself or possibly with the help of distributed data acquisition units, gathers information received from the network elements, through techniques such as polling or event trapping, in support of performing centralized functions such as determining the topology or operational status of the entire network or the root cause of network faults. Such centralized, hierarchical systems in which raw or formatted information is processed at a master server ultimately suffer from exhaustion of computation resources and poor response times. A necessary requirement of such centralized network management architectures is that the network management server “see” the entire network and thus be able to receive information from or regarding every element on the network and manage every such element as necessary. Other network management solutions that partition a network into multiple domains, with each domain being separately managed by a central server, do not offer a clear way of integrating cross-domain and end-to-end information, and are therefore not viewed as a full solution, or transform into a multi-hierarchy, centralized bottleneck.
Centralized network management systems suffer particularly when dealing with network surveillance and provisioning. In the event of a network fault, such as if a link between network elements falls, the fault would typically be detected by a polling unit which would then report the fault to the network management server which would determine the root cause of the fault, those network elements that are affected by the fault, and a course of action. As the number of faults increases, the increasing complexity and load of the required computation would eventually result in a failure of the central server and in faults not being handled. End-to-end provisioning and configuration requests that are carried out centrally would likewise suffer from increased multi-element multi-layer computation load and complexity. This problem is compounded in partitioned systems where part of the network suffers, as each centralized server does not see the entire network, which may be critical in handling cross-partition faults or provisioning.
Hence, computer network architectures that employ centralized network management are not easily scalable. Thus, as the number and complexity of network elements increases, and as provisioning procedures grow increasingly complex as the network diversifies, the central network management server will ultimately fail as its capacity to receive and process information from all network elements is exceeded.